Biochemical networks are meshes of homologous and non-homologous proteins. The "small world" topology - often scale free and in which a small number of hub nodes display extraordinarily high connectivity - is detected in the network models generated from omics results. Genomic basis of the scale-free topology - how to deduce this topology from genomic sequences - remains an open question. This proposal initiates an attempt to find a footing for this topology in genomic sequences. The focus is functional diversification of paralogous proteins and the formation of parallel pathways in the networks, in which the intrinsically disordered protein (IDP) segments is hypothesized to play preeminent roles. Our specific aims are as follows. 1: Quantifying parallel pathways in biochemical networks. Our preliminary studies suggest paralogous proteins diverge in their functional specificity to form parallel pathways. The proteome sequences would be clustered into families and each protein assigned to a numerical family ID. Biochemical network models would then be annotated with this numerical format. Subsequently, parallel pathways can be visualized and quantified by analysis combinatorial patterns of these numerical IDs. 2: Roles of disordered regions in the topology of biochemical networks. It is hypothesized that IDPs are crucial for functional diversification of paralogous proteins. This hypothesis will be tested by a combination of genome wide IDP analysis, comparative genomic analysis as well as experimental verification. 3: Scale-free distribution and multi-cellularity. The exponent constant in power-law distribution varies across species. This constant would be determined for specific tissue/cell types in order to explain this variation from single cell species to multi-cellular species. The roles of disordered regions in functional diversification of paralogous proteins in multi-cellular species would also be investigated.